ALBERT

Description: The 4th Evolving and Sustaining Ocean Best Practices Workshop was held online during the period 17-30 September 2020, addressing community needs for advanced method development and implementation in ocean observations, data management and application. The proceedings for the subject workshop are provided in 2 volumes. Volume 1 addresses the meeting overview, and Volume 2 - Annexes includes the complete Working Group reports.

Description: Report on European glider network coordination (Best Practices, OceanGliders, metadata and data management

Description: Best practices for eulerian observatories

Description: Harmonisation data management procedures and implementing FAIR principles with the target to serve the data infrastructures: Copernicus Marine Service and EMODnet (first stage) as well as SeaDataNet and historical National Oceanographic Data Centres (later stage)

Description: This deliverable reports on the achievements of the EuroSea project in developing targeted indicators co-designed with demonstrators (WPs 5–7) and forecasts (WP4). For this, the indicators implemented are expressed in term of Essential Ocean/Climate Variables (EOVs/ECVs) together with their requirements. The co-development undertaken address ocean indicators for all range of scales: from the large, basin scale to the regional and local scales. Such approach as well as the proposed solution to focus, at regional/local scales, on EEZs, represent one of the innovative results of EuroSea that will help to rationalize risks assessments and guide environmental management approaches in European Seas.

Description: This deliverable is intended to give an overview of the EuroSea actions at the interface between science and policy, ensuring the EuroSea results are useful for policy and decision-makers both at the EU, regional, and national levels.

Description: Strong anisotropy of seismic velocity in the Earth’scrust poses serious challenges for seismic imaging. Where in situ seismic properties are not available the anisotropy can be determined from velocity analysis of surface and borehole seismic profiles. This is well established for dense, long-offset reflection seismic data. However, it is unknown how applicable this approach is for sparse seismic reflection data with low fold and short offsets in anisotropic metamorphic rocks. Here we show that anisotropy parameters can be determined from a sparse 3D data set at the COSC-1 borehole site in the Swedish Caledonides and that the results agree well with the seismic anisotropy parameters determined from seismic laboratory measurements on core samples. Applying these anisotropy parameters during 3D seismic imaging improves the seismic image of the high amplitude reflections especially in the vicinity of the lower part of the borehole. Strong reflections in the resulting seismic data show good correlation with the borehole-derived lithology. Our results aid the interpretation and extrapolation of the seismic stratigraphy of the Lower Seve Nappe in Jämtland and other parts in the Caledonides.

Description: The southern boundary of the Cayman Trough in the Caribbean is marked by the Swan Islands transform fault (SITF), which also represents the ocean-continent transition of the Honduras continental margin. This is one of the few places globally where a transform continental margin is currently active. The CAYSEIS experiment acquired an ∼165-km-long seismic refraction and gravity profile (P01) running across this transform margin, and along the ridge-axis of the Mid-Cayman Spreading Centre (MCSC) to the north. This profile reveals not only the crustal structure of an actively evolving transform continental margin, that juxtaposes Mesozoic-age continental crust to the south against zero-age ultraslow spread oceanic crust to the north, but also the nature of the crust and uppermost mantle beneath the ridge-transform intersection (RTI). The traveltimes of arrivals recorded by ocean-bottom seismographs (OBSs) deployed along-profile have been inverse and forward modelled, in combination with gravity modelling, to reveal an ∼25-km-thick continental crust that has been continuously thinned over a distance of ∼65 km to ∼10 km adjacent to the SITF, where it is juxtaposed against ∼3-4-km-thick oceanic crust. This thinning is primarily accommodated within the lower crust. Since Moho reflections are only sparsely observed, and, even then, only by a few OBSs located on the continental margin, the 7.5 km s-1 velocity contour is used as a proxy to locate the crust-mantle boundary along-profile. Along the MCSC, the crust-mantle boundary appears to be a transition zone, at least at the seismic wavelengths used for CAYSEIS data acquisition. Although the traveltime inversion only directly constrains the upper crust at the SITF, gravity modelling suggests that it is underlain by a higher density (〉3000 kg m-3) region spanning the width (∼15 km) of its bathymetric expression, that may reflect a broad region of metasomatism, mantle hydration or melt-depleted lithospheric mantle. At the MCSC ridge-axis to the north, the oceanic crust appears to be forming in zones, where each zone is defined by the volume of its magma supply. The ridge tip adjacent to the SITF is currently in a magma rich phase of accretion. However, there is no evidence for melt leakage into the transform zone. The width and crustal structure of the SITF suggests its motion is currently predominantly orthogonal to spreading. Comparison to CAYSEIS Profile P04, located to the west and running across-margin and through 10 Ma MCSC oceanic crust, suggests that, at about this time, motion along the SITF had a left-lateral transtensional component, that accounts for its apparently broad seabed appearance westwards.

Description: This report presents the results of Task 7.3 on “Development of BGC-Argo data quality validation based on an integrative multiplatform approach”. Observing changes in ocean conditions on the spatiotemporal scales necessary to constrain carbon uptake is a challenge. Defined as an Essential Ocean Variable (EOV) by the Global Ocean Observing System (GOOS, e.g., Tanhua et al., 2019), pH is relevant to assess numerous crucial questions regarding the oceanic evolution in response to the current global changes. However, the large spatiotemporal variability of this carbonate system parameter requires sustained observations to decipher trends and punctual events. Within this scope, numerous pH sensors suitable for deployments both on autonomous observing tools and fixed stations have been developed. Nevertheless, as interpreting changes relies on accurate data, and because offsets or drifts in pH data might appear in response to changes in the sensor k0 constant, a consistent and rigorous correction procedure to quality-control and process the data has been implemented. This report presents the application of this method to pH data acquired by BGC-Argo floats launched in the Tropical Atlantic area.

Description: This deliverable provides an overview of EuroSea outcomes related to interior ocean carbon variability in deep convection areas in order to assess the linkage of these processes for the use in national climate action (NCA) plans delivered in the framework of the Paris Agreement. In summary, large-scale connectivity in the ocean does not allow clear delineation of patterns of regional carbon uptake across national boundaries, limiting an assessment of the Exclusive Economic Zones (EEZ) in light of NCA plans. This problem becomes already clear by a simple scale estimation: considering sluggish, open ocean (away from continental boundaries) advection speeds of 2 cm/s result in a “relocation” of any water parcel by roughly 630 km per year (or 3150 km in 5 years Paris Agreement carbon auditing period) and crossing national borders easily. Knowing changes in the global ocean carbon uptake is of great importance for the preparation of NCA plans. This is because the NCA plans are motivated by the globally averaged atmospheric CO2 concentration, which is the sum of all sources and sinks and including the ocean sink. In case of decrease in the oceanic sink (e.g., IPCC, 2021), more CO2 will remain in the atmosphere and consequently nations will need to formulate their NCA plans with increased ambition in order to meet the CO2 target defined in the Paris Agreement. In this deliverable key approaches for the assessment of the global ocean carbon uptake have been applied to ocean areas. The observational requirements for applying statistical approaches (i.e., artificial neural networks, Fourrier et al., 2020) to reconstruct dissolved inorganic carbon (DIC) from oxygen, nutrient and hydrographic data are analysed. It is shown that even small changes in the DIC content determined in this way can be linked to anthropogenic increases in atmospheric carbon (Cant). Furthermore, it has been shown that multilinear regression techniques can be used to produce maps of ocean surface carbon fluxes at very high spatial resolution, which in turn can provide a much more accurate estimate of regional CO2 uptake (or release). Finally, a quantification of the redistribution of dissolved gases in boundary current systems could be investigated by following recommendations for observational methods stemming from this deliverable. This deliverable recommends improvement of carbon sampling in all nations EEZ regions and following global standards. Because the objective targets a global assessment, the data must be disseminated rapidly and in a FAIR fashion to enable further global integration (e.g., global carbon budget). A need for defining responsibilities for such global integration and the resourcing is required. It is recommended to make use of statistical methods to create surface and interior carbon parameter distributions via multiparameter approaches with a sufficient amount of reference data (e.g., co-located DIC, oxygen, nutrients, chlorophyll-a, hydrography). In the light of the ongoing crisis related to global availability of the Certified Reference Materials (CRMs) for carbonate system measurements, provision of European-produced material becomes critical to enable traceability of future measurements. Nations should be encouraged to provide appropriate resources by means of corresponding European directives. Example for such national commitments is the collection of reference data in the framework of the Common Fisheries Policy.

Description: The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with annual updates. SOCAT aims to provide data with the highest possible quality for carbon data – consistent quality control (QC) is essential in achieving this primary goal of SOCAT. Currently there are various steps of quality control, and within this task of EuroSea we aimed to develop an operational implementation of QC as a showcase for data within SOCAT from the European Research Infrastructure Integrated Carbon Observing System. The aim within EuroSea is to increase the Technology Readiness Level (TRL) from 5 (Technology validated in relevant environment) to 7 (system prototype demonstration in operational environment) for relevant ICOS data for direct submission to SOCAT. This was achieved by creating automated quality control into the ICOS state-of-art-software QuinCe, a web-based tool for processing and quality control of data from in situ sensors and underway instruments that is used for first and second level quality control for operational ICOS stations. One important aspect of SOCAT is the assessment of data quality, to ensure that all published data is fit for purpose and manual eyes-on QC is currently essential to lower uncertainties. Currently, this assessment consists of evaluating the metadata of each dataset to ensure that the correct Standard Operational Procedures (SOPs) have been followed during data collection, that the system setup is correct, instruments are calibrated and in addition examining data to ensure they are of good quality. SOCAT consists of three steps of QC: 1.) QC while data is being ingested; 2.) Eyes-on QC by regional experts and 3.) QC for the entire dataset defining the uncertainty based upon the submitted metadata and within this task it has been shown that certain parts of this QC process can be automated while other levels bear challenges if a higher level of TRL is aimed for.